TWI400062B - Medical devices that record physiological signals - Google Patents

Description

Medical device capable of recording physiological signals

The invention relates to a medical device, in particular to a medical device capable of recording physiological signals.

According to the present, cerebrovascular diseases and heart diseases have been highly valued in recent years, and cerebrovascular diseases and heart diseases are the only major causes of death after malignant tumors. At present, the number of cerebrovascular diseases is increasing every year. Heart disease, diabetes, and high blood pressure are the main accomplices of stroke. Such high-risk diseases deserve our attention and concern.

Coronary heart disease is one of the most common chronic diseases, and its incidence is second only to hypertension and stroke. There are many reports in the literature that coronary heart disease combined with cerebral vascular stenosis, resulting in neuropathy after coronary artery bypass or balloon dilation, including stroke or long-term mental deterioration. There are also evidences of cross-flow disorders on the brain scan of nuclear medicine. On the other hand, after coronary surgery, patients often develop mental deterioration and other neurological complications. The cause is often attributed to a small infarction caused by arrhythmia (especially atrial fibrillation) caused by coronary heart disease. We believe that other important reasons that are often overlooked are that coronary heart disease patients have cerebrovascular obstruction.

When a patient with cerebrovascular disease has an organic disease or a functional abnormality in the brain, the electrical physiology of the nerve cell is affected, and various brain wave changes are generated. When the brain produces lesions, the necrosis of the nerve cells loses the original electrical activity, and in the case of a large cerebral infarction, the brain wave may disappear or the amplitude may decrease. Local undulations of θ and δ are generated at and around the cerebral half-stage lesions, usually polymorphic delta (PDA). Localized Xu waves may replace the original normal brain waves, and may also be mixed with the original background brain waves. In patients with cerebral apoplexy, changes in brain waves may have polymorphic high amplitude Xu waves, loss of basic background rhythm waves, intermittent regular δ waves, etc. Some epileptic brain waves may occur in patients with acute stroke. When a blood clot is present in the brain, a flat type of electric wave whose amplitude is greatly reduced appears. Cerebral vascular stenosis can lead to hypoxia in the brain. EEG changes are affected by the severity of hypoxia and its transient. In the most severe cases, α-coma (a-coma), burst-repressed brain waves ( Burst-suppression pattern) or flat EEG.

The heart function is like a pump. When a patient with cardiovascular disease has any disease caused by valve damage and increases the burden on the heart, it will cause symptoms of heart disease, whether it is due to resistance caused by stenosis or blockage of blood leakage. Incomplete changes cause the blood to flow back and forth between the atrium and the ventricles, causing the burden of the heart itself to increase. Once the burden is aggravated, symptoms of heart failure are present. According to its own degree of stenosis, or the degree of incomplete locking, it produces different degrees of symptoms. When there is a problem with any of the valves, it will cause the ventricles to slowly expand or become thick, and then the heart itself will be burdened, so that the blood with extremely high oxygen content cannot be supplied to the whole body. At this time, blood flow to the brain or blood flow to the lower limbs is insufficient, and symptoms of hypoxia in the brain are produced. When the blood is hypoxic, the heart rate increases, and the cardiac output and blood pressure increase. Blood pressure, heart rate, and cardiac output decreased during severe hypoxia, and heart rhythm disorders, ventricular fibrillation, and cardiac arrest may occur. Therefore, when the blood vessels are narrow, the heartbeat interval in the electrocardiogram will be affected by the severity of hypoxia and different heart rate changes, and the brain will also have abnormal brainwaves due to the lack of oxygen in the foot.

When the heart is ischemic, the blood delivered to the brain is insufficient, resulting in hypoxia in the brain. The severity of hypoxia in the brain and the time of hypoxia are different for brain waves. Alpha-coma (α-com), burst-repressed brain waves or flat EEG. When the heart rhythm is not complete, the blood may cause a thrombus condition. When a small blood clot in the blood enters the brain, it may cause cerebral blood to be embolized, causing the brain wave to exhibit a local slow wave.

When the brain is in a state of ischemia or hemorrhage, the brain will adjust the activity of the autonomic nervous system, so that the heart rate is accelerated, the breathing is rapid, and the heart is pressurized to deliver more oxygen, which restores the oxygen content of the brain.

In order to thoroughly clarify the history and risk factors of such patients, patients with coronary heart disease and cerebral vascular stenosis (group 1), and surgery for severe coronary heart disease or balloon dilatation The patient (second group) tried to design and produce a 24-hour portable synchronous ECG brain wave recording instrument, and used the obtained signals to determine a relationship between them. The primary goal is the temporal correlation between the brainwave signal and the ECG signal. Since then, I hope to establish a regression model of the correlation coefficient based on this relationship. I believe that such a model will not only effectively explain the neurological complications after the above surgery, but also be an important basis for preventing such complications. In addition, for the unexplained ischemic stroke (third group), long-term is considered to be associated with paroxysmal arrhythmia (especially atrial fibrillation) and transient intracardiac thrombosis. Such paroxysmal atrial fibrillation, although not yet known by routine electrocardiogram, may cause such ischemic stroke. I hope that I can use this 24-hour portable synchronous ECG brain wave recording instrument to clarify this problem.

Therefore, how to solve the above problems and propose a novel medical device capable of recording physiological signals, which can simultaneously record the accuracy of the electrocardiogram and the brain wave signal on the screen of the same computer to view the electrocardiogram signal and the brain wave signal, so as to facilitate the doctor to carry out the heart. Correlation analysis between electrical signal (ECG) and brain wave signal (EEG).

One of the objects of the present invention is to provide a medical device capable of recording physiological signals, which can simultaneously detect and record the ECG signals and brain wave signals of the human body, so as to facilitate analysis of diseases by doctors.

One of the objects of the present invention is to provide a medical device capable of recording a physiological signal, which can analyze the correlation between the human body's electrocardiogram signal and the brain wave signal, so as to facilitate the analysis of the disease by the doctor.

The medical device capable of recording physiological signals of the present invention comprises a brain wave detecting circuit, an electrocardiogram detecting circuit, a micro control circuit and a storage circuit. The brain wave detection circuit detects the brain of the human body to generate a brain wave signal, and the electrocardiogram detection circuit detects the heart of the human body to generate an ECG signal, and the micro control circuit receives the brain wave signal and the ECG signal to generate a control signal. The storage unit stores the brain wave signal and the ECG signal according to the control signal. Among them, the ECG signal is associated with the brain wave signal.

Furthermore, the medical device capable of recording the physiological signal of the present invention further comprises an analyzing unit for receiving the brain wave signal and the electrocardiogram signal according to the control signal to analyze the brain wave signal and the electrocardiogram signal, and generating an analysis signal for the doctor to perform. Analyze the disease.

In order to provide a better understanding and understanding of the structural features and the efficacies of the present invention, please refer to the preferred embodiment and the detailed description as follows: please refer to the first figure, which is A block diagram of a preferred embodiment of the invention. As shown in the figure, the medical device capable of recording physiological signals includes a brain wave detecting circuit 10, an electrocardiogram detecting circuit 12, an analog digital converting circuit 20, 22, a micro control circuit 30 and a storage device. Unit 40. The brain wave detecting circuit 10 is configured to detect a brain of a human body to generate a brain wave signal, wherein please refer to the second figure, which is a block diagram of the brain wave detecting circuit of the present invention, as shown in the figure. The brain wave detecting circuit 10 includes an electrode module 100, a first discharging circuit 110, a filtering circuit 120 and a second amplifying circuit 130. The electrode module 100 comprises six electrodes, which are evenly distributed in the brain of the human body (as shown in the third figure), that is, an average distribution of six points Fp1, Fp2, F3, F4, C3, and C4 in the brain, and is divided into six points. Left and right ends, left end with Fp1, F3, C3 as positive (Vin+), A1 as negative (Vin-), right end with Fp2, F4, C4 as positive (Vin+), A2 as negative (Vin-), hereinafter As a reference grounding point. In this way, the brain wave signal of the brain can be detected on average to fully understand the state of various parts of the brain.

The first amplifying circuit 110 is an instrumentation amplifier. Since the brain wave signal is very small, the signal is easily unstable, and the brain wave is often not measured. Therefore, the first amplifying circuit 110 receives the brain wave signal detected by the electrode module 100. To amplify the weak physiological signal, the brain wave signal. The filter circuit 120 receives the brain wave signal amplified by the first amplifying circuit 110 to filter the noise of the brain wave signal. The filter circuit 120 further includes a high pass filter 122, a low pass filter 124 and a band reject filter 126. The high-pass filter 122 receives the brain wave signal amplified by the first amplifying circuit 110, and filters out the components of the low-frequency drift of the brain wave signal to avoid low-frequency interference during measurement. The high pass filter 122 is a Butterworth low pass filter. Because it takes into account the components of the brainwave signal as much as possible, and removes unnecessary high-frequency noise. Therefore, a low-pass filter 124 is further disposed, which receives the high-frequency component of the brain wave signal filtered by the high-pass filter 122 to filter out the low-frequency drift component of the brain wave signal, thereby avoiding high-frequency interference during measurement. Mainly for 60 Hz home appliance noise. The frequency component of the brainwave signal falls at about 1~30Hz, so the cutoff frequency is set at 30Hz. On the one hand, the 60Hz signal is filtered out first, as a 60Hz pilot filter. The low pass filter 124 is a Butterworth fourth-order low pass filter. The rejection filter 126 filters a noise frequency of the brain wave signal filtered by the low pass filter 122 to filter the power noise of the noise frequency of 60 Hz. The second amplifying circuit 130 receives the brain wave signal filtered by the filter circuit 120 and amplifies the brain wave signal.

The electrocardiogram detecting circuit 12 detects the heart of the human body to generate an electrocardiogram signal, wherein the electrocardiogram detecting circuit 12 causes the electrodes to be applied to the RA and LA of the human body (as shown in the fourth figure), and the brain wave detection The measuring circuit 10 shares the chin as a reference grounding point. Since the circuit principle of the electrocardiogram detecting circuit 12 and the brain wave detecting circuit 10 are the same, no further comments are made.

The analog digital conversion circuits 20 and 22 respectively receive the brain wave signal and the electrocardiogram signal to respectively convert the analog signals of the brain wave signal and the electrocardiogram signal into digital signals, and transmit the signals to the micro control circuit 30. The micro control circuit 30 receives the digital signals of the brain wave signal and the electrocardiogram signal to generate a control signal. The storage unit 40 receives the control signal to store and record the brain wave signal and the ECG signal. Moreover, since the medical device of the present invention is small in size, it is convenient to carry and can simultaneously measure and record brain wave signals and ECG signals.

In addition, the medical device capable of recording physiological signals of the present invention further includes a display device 42 and an input unit 44. The display device 42 is coupled to the micro control circuit 30 for receiving the ECG signal and the brain wave signal for displaying the ECG signal and the brain wave signal in real time, and allowing the user to select the physiological signal to be displayed, and displaying the screen on the display device 42. The upper left corner shows the status of the current medical device, telling the user that the display device 42 is currently in standby, transmitting data, or capturing signals (as shown in Figure 5). The display device 42 is a liquid crystal display (LCD).

Furthermore, an interface menu of the display device 42 is provided for the user to perform an operation with the input unit 44. The input unit 44 is coupled to the micro control circuit 30, and transmits an input signal to control the operation of the micro control circuit 30. The input unit 44 is a keyboard device for the user to communicate with the medical device, so that the user can easily use the keyboard. The input controls the medical device. As shown in the sixth figure, the function of the keyboard device is 0: start capturing signal, 1: stop capturing signal, 2: transmission, 3: system reset, 4: selecting channel.

The analyzing unit 50 receives the brain wave signal and the ECG signal according to the control signal, analyzes the correlation between the brain wave signal and the ECG signal, and generates an analysis signal for the doctor to analyze the disease. Please refer to the seventh diagram and the eighth diagram together, which are respectively a block diagram and an analysis unit of the analysis unit of the present invention for analyzing the flow chart of the electrocardiogram signal and the brain wave signal. As shown, the analysis unit 50 of the present invention includes a first operation unit 54, a second operation unit 56, and an integration unit 58. The first operation unit 54 receives the ECG signal and calculates the ECG signal to generate at least one ECG parameter, and the central electrical parameters are α parameter (α activity), β parameter (β activity), δ parameter (δ activity) and θ parameter. (θ activity). Furthermore, the first arithmetic unit 54 calculates the electrocardiogram signal to know the electrocardiogram parameter. The following is described in conjunction with the eighth figure. First, after the first arithmetic unit 54 receives the electrocardiogram signal (step S10), the ECG signal is used. Characterization (step S11), the purpose is to facilitate us to find the position of the R wave in the ECG signal, and then calculate the R-R interval (R-R Interval) time (as in step S12), and re-sample through step S13. After (Resample), the electrocardiographic parameter, that is, the parameter in the heart rate variability, is obtained by fast Fourier transform (FFT) via step S15. The time synchronization is compared with the spectral components of the brain waves (step S18). Since the present invention employs a fast Fourier transform of 2048 points (step S14) in this embodiment, it is necessary to collect 2048 sample points before the power spectrum can be calculated. After calculating the heart rate variability power spectrum, several peaks can be found in the power spectrum diagram in the frequency range of 0 to 0.4 Hz. In this study, the energy in the frequency band from 0.04 to 0.15 Hz is defined as the low band energy. (low frequency power, LFP), additionally, the energy in the frequency band of 0.15 to 0.4 Hz is defined as high frequency power (HFP), and 0 to 0.5 Hz is defined as the total frequency band TP_hrv (hrv total power).

The second operation unit 54 calculates the brain wave signal to generate at least one brain wave parameter, that is, the second operation unit 54 uses the original signal of the brain wave, and cooperates with the first operation unit 52 to adopt 2048 points (as shown in step S31). Fast Fourier transform (such as step S32), after obtaining the power spectrum, then move 40 points backwards and then take a fixed length to get the next piece of data, so that the time resolution of 0.2 seconds can be reached, and the end of 30 heartbeats (such as step S20) Shown). These obtained power spectra are then averaged (step S35) to calculate brainwave parameters, wherein the energy in the frequency band of 0.4 to 4 Hz is defined as the delta parameter (δ activity), in the frequency band of 4 to 8 Hz. The energy is defined as the θ parameter (θ activity), the energy in the frequency band of 8 to 12 Hz is defined as the α parameter (α activity), and the energy in the frequency band of 12 to 30 Hz is defined as (β activity), in the frequency band of 0 to 30 Hz. The energy is defined as TP_eeg (EEG total power), and a parameter data is calculated for every 30 heartbeats. The parameters include RR interval (RR Interval), heart rate variability (HRV), LFP, HFP, TP_hrv, and δ, θ of brain waves. α, β activity, TP_eeg parameters. Repeat the above steps, each time you update 30 heartbeats, you can get the brainwave time-frequency domain power spectrum analysis. The integration unit 58 receives and integrates the electrocardiographic parameters and the brain wave parameters to generate at least one related parameter. That is, Pearson correlation analysis is used to find the Pearson correlation coefficient, which is a non-directional coefficient from -1.0 to 1.0, which is used to reflect the degree of linear relationship between the two data sets.

According to the above, the correlation between the β parameter of the whole person's sleep and the RR interval is analyzed, and the correlation is -0.749, and the correlation between the δ parameter of the whole person's sleep and the low-band energy (LF) is analyzed. The correlation also has -0.477. Although the correlation between δ parameter and LF is only -0.447, its δ parameter has a considerable degree of negative correlation with the overall trend of LF. Therefore, in this embodiment, the δ parameter and the LF are taken out to analyze the correlation coefficient by event, and an event threshold is set for each, the δ parameter threshold is 0.20, and the LF is set to 0.06, which is respectively compared with the threshold, if the valve is exceeded. The value is set to 1, and is set to 0 when the threshold is not exceeded, meaning that the threshold value is exceeded when the δ parameter event occurs, and when the LF is active. After the calculation, the correlation analysis was performed, and the results of the Pearson correlation coefficient were -0.608, which showed a high negative correlation. It may be that the sympathetic nerves are inhibited when they are asleep, and the sympathetic nerves are activated during REM sleep. In this way, the correlation between the electrocardiographic parameters of the normal person and the brain wave parameters is provided to the doctor for analyzing the abnormal state of the human body.

In addition, the medical device of the present invention can be a portable medical device for continuously recording the brain wave signal and the electrocardiogram signal of the human body, and then coupled between the micro control circuit 30 and the analyzing unit 50 through a transmission interface 52 to transmit brain waves. The signal and the ECG signal are sent to the analysis unit 50. The analysis unit 50 can be disposed in a computer system to analyze the correlation between the brain wave signal and the ECG signal. Thus, by long-term recording of the brain wave signal and the ECG signal of the human body. The medical device of the present invention is convenient for the user to record at home, and then provided to the doctor for analysis and judgment of the disease of the patient. Among them, the transmission media The surface 52 is a Peripheral Component Interconnect (PCI) digital output card, a universal serial bus (USB), a 1394 specification transmission interface, and a wired area network (IEEE802. 3) The transmission interface, the transmission interface of an infrared specification (IrDA) or the transmission interface of a Bluetooth specification. The above is only an example of the transmission interface provided by the embodiment, but is not limited to the above-mentioned transmission interface.

In summary, the medical device capable of recording a physiological signal of the present invention uses a brain wave detecting circuit and an electrocardiogram detecting circuit to simultaneously detect a brain wave signal and an electrocardiogram signal of the human body, and The analysis unit analyzes the correlation between brainwave signals and ECG signals to facilitate analysis of the disease by doctors.

The invention is a novelty, progressive and available for industrial use, and should meet the requirements of the patent application stipulated in the Patent Law of China, and the invention patent application is filed according to law, and the prayer bureau will grant the patent as soon as possible. prayer.

However, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and the shapes, structures, features, and spirits described in the claims are equivalently changed. Modifications are intended to be included in the scope of the patent application of the present invention.

1‧‧‧ human body

10‧‧‧ brain wave detection circuit

100‧‧‧electrode module

110‧‧‧First amplification circuit

12‧‧‧ ECG detection circuit

120‧‧‧Filter circuit

122‧‧‧High-pass filter

124‧‧‧Low-pass filter

126‧‧‧Rejection filter

130‧‧‧Second control circuit

20‧‧‧ analog digital conversion circuit

22‧‧‧ analog digital conversion circuit

30‧‧‧Micro Control Circuit

40‧‧‧ storage unit

42‧‧‧ display device

44‧‧‧ Input unit

50‧‧‧Analysis unit

52‧‧‧Transportation unit

54‧‧‧First arithmetic unit

56‧‧‧Second arithmetic unit

58‧‧‧Integrated unit

The first figure is a block diagram of a preferred embodiment of the present invention; the second figure is a block diagram of the brain wave detecting circuit of the present invention; the third figure is a schematic diagram of the brain wave electrode setting of the present invention; The schematic diagram of the display device of the present invention; the fifth diagram is a schematic diagram of the display interface of the display device of the present invention; the sixth diagram is a schematic diagram of the function of the button of the input unit of the present invention; And the eighth figure is a flow chart of analyzing the ECG signal and the brain wave signal by the analyzing unit of the present invention.

1‧‧‧ human body

10‧‧‧ brain wave detection circuit

12‧‧‧ ECG detection circuit

20‧‧‧ analog digital conversion circuit

22‧‧‧ analog digital conversion circuit

30‧‧‧Micro Control Circuit

40‧‧‧ storage unit

42‧‧‧ display device

44‧‧‧ Input unit

50‧‧‧Analysis unit

52‧‧‧Transportation unit

Claims (18)

A medical device capable of recording a physiological signal, comprising: a brain wave detecting circuit for detecting a brain of a human body to generate a brain wave signal; an ECG detecting circuit for detecting the heart of the human body to generate an electrocardiogram signal The brain wave detecting circuit and the ECG detecting circuit synchronously capture the brain wave signal and the ECG signal; a micro control circuit receives the brain wave signal and the ECG signal to generate a control signal; Receiving the control signal to store the brain wave signal and the ECG signal; a display device coupled to the micro control circuit to receive the ECG signal and the brain wave signal to display the ECG signal and the brain wave And an analyzing unit, according to the control signal, receiving the brain wave signal and the ECG signal, analyzing the brain wave signal and the ECG signal, generating an analysis signal, and having: a first operation unit, the operation The ECG signal generates at least one ECG parameter; a second computing unit calculates the brain wave signal to generate at least one brain wave parameter; and an integration unit receives and integrates the ECG parameter and the brain wave parameter Generating at least a parameter related to the system parameters and the degree of anti ECG should be a linear relationship between the specifications of the electroencephalogram; wherein associated with the ECG signal to the brain wave signal. The medical device according to claim 1, wherein the relevant parameter is generated by the integrating unit respectively setting a threshold value of the electrocardiographic parameter and the brain wave parameter to transmit the ECG parameter or the brain Whether the wave parameter exceeds the threshold provides a non-directional coefficient of -0.1 to 1.0. The medical device of claim 1, further comprising: a transmission interface coupled between the micro control circuit and the analysis unit, and transmitting the brain wave signal and the ECG signal to the analysis unit. The medical device of claim 3, wherein the transmission interface is a Peripheral Component Interconnect (PCI) digital output card, a 1394 specification transmission interface, and a wired area network (IEEE 802. 3) transmission interface, an infrared Line specification (IrDA) transmission interface or a Bluetooth transmission interface. The medical device according to claim 1, wherein the electrocardiographic parameter is a low frequency band energy of a total frequency band (Total power, TP) with a frequency between 0 and 0.5 Hz and a frequency between 0.04 and 0.15 Hz. (Low Frequency power, LFP) or high frequency power (HFP) with a frequency between 0.15 and 0.4 Hz. The medical device according to claim 1, wherein the brain wave parameter is an α parameter with a frequency between 8 and 12 Hz, a β parameter with a frequency between 12 and 30 Hz, a δ parameter with a frequency between 0.4 and 4 Hz, and The θ parameter with a frequency between 4 and 8 Hz. The medical device of claim 1, further comprising: an analog-to-digital converter, wherein the analog signal of the brain wave signal is converted into a digital signal and transmitted to the micro control circuit. The medical device of claim 1, further comprising: an analog-to-digital converter that converts the analog signal of the ECG signal into a digital signal and transmits the signal to the micro control circuit. The medical device of claim 1, further comprising: an input unit coupled to the micro control circuit to transmit an input signal to control the operation of the micro control circuit. The medical device of claim 1, wherein the display device is a liquid crystal display (LCD). The medical device of claim 1, wherein the brain wave detecting circuit further comprises: an electrode module for attaching and detecting the brain of the human body to generate the brain wave signal; a circuit for receiving and amplifying the brain wave signal; a filter circuit receiving the brain wave signal amplified by the first amplifying circuit and filtering the brain wave signal; and a second amplifying circuit receiving the filter filtered by the filter circuit Brain wave signal and amplify the brain wave signal. The medical device of claim 11, wherein the electrode module comprises six electric devices pole. The medical device of claim 11, wherein the filtering circuit further comprises: a high-pass filter for filtering a low-frequency component of the brain wave signal; a low-pass filter filtering the high-pass filter for filtering a high frequency component of the brain wave signal; and a band rejection filter that filters a noise frequency of the brain wave signal filtered by the low pass filter. The medical device of claim 13, wherein the frequency of the noise frequency is 60 Hz. The medical device of claim 1, wherein the electrocardiographic detection circuit further comprises: an electrode module for attaching and detecting the heart of the human body to generate the electrocardiogram signal; a first amplifying circuit Receiving and amplifying the ECG signal; a filter circuit receiving the ECG signal amplified by the amplifier circuit and filtering the ECG signal; and a second amplification subtraction circuit receiving the ECG filtered by the filter circuit Number and enlarge the ECG signal. The medical device of claim 15, wherein the filtering circuit further comprises: a high-pass filter for filtering a low-frequency component of the ECG signal; and a low-pass filter for filtering the core of the high-pass filter after filtering a high frequency component of the electrical signal; and a rejection filter that filters a noise frequency of the ECG signal filtered by the low pass filter. The medical device of claim 16, wherein the frequency of the noise frequency is 60 Hz. The medical device of claim 1, wherein the storage unit is a flash memory.